Advances in networking and computing technologies have enabled the transformation of computers from low performance/high cost devices capable of performing basic word processing and computing low-level mathematical computations to high performance/low cost machines capable of a myriad of disparate functions. For example, a consumer level computing device can be employed to aid a user in paying bills, tracking expenses, communicating nearly instantaneously with friends or family across large distances by way of email, obtaining information from networked data repositories, and numerous other functions/activities. Computers and their associated peripherals have thus become a staple in modern society, utilized for both personal and business activities.
The Internet in particular has provided users with a mechanism for obtaining information regarding any suitable subject matter. For example, various web sites are dedicated to posting text, images, and video relating to world, national, and/or local news. A user with knowledge of a Uniform Resource Locator (URL) associated with one of such web sites can simply enter the URL into a web browser to be provided with the web site and access content. Another conventional manner of locating desired information from the Internet is through utilization of a search engine. For instance, a user can enter a word or series of words into a search field and initiate a search engine (e.g., through depression of a button, one or more keystrokes, voice commands, etc.). The search engine then utilizes search algorithms to locate web sites related to the word or series of words entered by the user into the search field, and the user can then select one of the web sites returned by the search engine to review related content.
As more and more people have begun to utilize the Internet, it has become apparent that revenue opportunities exist for small and large businesses alike. For instance, many retail companies utilize the Internet to sell goods online, thereby reducing costs associated with managing and maintaining a store location, providing an ability to centralize inventory, and various other similar benefits that result in decreased costs that are passed on to customers. Given this increased use of the Internet for generating business and/or revenue, it has also become apparent that the Internet can be utilized as an advertising mechanism. In one example, an individual who enters the term “flower” into a search engine may be interested in purchasing flowers—thus, it is beneficial for a company that sells flowers to advertise to that user at the point in time that the user is searching for a relevant term. Oftentimes users who are searching for information will see related advertisements and click on such advertisements to purchase flowers, thereby creating business for the flower retailer. Furthermore, the search engine is provided with additional revenue by selling advertisement space for a particular period of time to a retailer when a relevant term, such as, for example, the term “flower,” is utilized as a search term.
Conventionally, advertising space relating to search terms provided to a search engine is bought or sold in an auction manner. More specifically, a search engine can receive a query (from a user) that includes one or more search terms that are of interest to a plurality of buyers. The buyers can place bids with respect to at least one of the search terms, and a buyer that corresponds to the highest bid will have their advertisement displayed upon a resulting page view. Bidding and selection of a bid can occur within a matter of milliseconds, thereby not adversely affecting usability of the search engine. Thus, two or more competing bidders can bid against one another within a limited time frame until a sale price of advertising space associated with one or more search terms in the received query is determined. This bidding is often accomplished by way of proxies (e.g., computer component) that are programmed with a demand curve for specific search term(s). As alluded to above, auctioning advertising space associated with search terms is a substantial source of revenue for search engines, and can further be a source of revenue for advertisers.
Because of the potential of a significant boost in revenue from advertising with search terms, it is very likely that a business will attempt to associate as many search terms as possible to their advertisements, even words that have no relevancy to the search terms themselves. This is typically attempted for two reasons—first, to increase exposure of the advertisement, and, second, to exclude the competition from being able to advertise. However, by allowing associations with search terms of non-relevant advertisements, users typically become quickly dissatisfied with the search engine and switch to another search engine or become hostile towards a particular advertiser for constantly displaying irrelevant advertisements every time they search. To avoid these issues, oftentimes “relevancy standards” are utilized to determine if a search term is relevant enough to allow it to be associated with a particular advertisement and/or business. Current technology to determine relevancy is very cumbersome and typically requires models that must be trained and retrained as the data changes and can only be implemented for a specific business relevancy standard. Since relevancy can change overtime (e.g., businesses add new lines, consumer trends change, words take on new meanings, etc.), current attempts to evaluate relevancy become very burdensome and time consuming to change.